भारत सरकारदूरसंचार विभागदूरसंचार अवभयांविकी कें द्र
Government of India
Department of Telecommunications
Telecommunication Engineering Centre
K.L. Bhawan, Janpath, New Delhi- 110001
No. 14-1/2023-C&B/TEC/AI-Robustness

Dated 18.10.2023

Subject: Standard for Assessing and Rating Robustness of Artificial Intelligence Systems in Telecom
Networks and Digital Infrastructure - reg.
Artificial intelligence (AI) and Machine Learning (ML) have gained significant traction acrossdiverse domains, including Healthcare, Agriculture, Smart Cities, Finance, and more. Governmentorganizations also deploy AI/ML for public services and e-governance. In the telecom industry, AI
enables real-time decision-making and plays a growing role in upcoming technologies such as IMT2030 (6G), satellite broadband, drone communication, and the Metaverse.
The telecom sector, crucial for information exchange and digital transformation, operates
within a complex ecosystem driven by AI. Here, paramount importance lies in robustness, signifying
AI's ability to perform reliably under diverse, unpredictable conditions. For the telecom networks anddigital infrastructure, where connectivity is indispensable, robust AI isn't a luxury; it's a necessity.
Developing a Responsible AI standard in telecom is imperative to ensure robustness and safety ofAI/ML systems. Robustness may encompass an AI system's response to adversarial attacks, scalability,resilience, safety, and more. Assessing robustness is vital to ascertain the AI system's trustworthinessand responsibility.
National Digital Communications Policy-2018 mandates the synergistic deployment andadoption of AI. The National Strategy for Artificial Intelligence #AIforAll, and the Approach Documents
for India, released by NITI Aayog, emphasise adoption of AI in a responsible manner in India, building
public trust in the use of AI, and creating frameworks for compliance with relevant AI standards andguidelines. Telecommunication Engineering Centre (TEC), as the technical wing of DoT and theStandards Setting Organisation (SSO) in the field of telecom and related ICT sectors, recently released
the Standard for Fairness Assessment and Rating of Artificial Intelligence Systems. Now, TEC proposes
to develop a voluntary standard for assessing and rating the robustness of AI systems in telecom
networks and digital infrastructure.
Accordingly, TEC is initiating stakeholder consultations and invites your inputs on the subject.
Your valuable contributions as per the enclosed template may be sent to avinash.70@gov.in anddircb2.tec-dot@gov.in, preferably by 15th November 2023 please. Your insights are highly appreciated.
This issues with the approval of Sr. DDG, TEC.

(Avinash Agarwal)
DDG (Convergence & Broadcasting)
Email: avinash.70@gov.inTo:
1. All stakeholders
Copy for kind information to:
1. CEO Niti Aayog
2. Secretary Telecom/ Agriculture/ DST/ Defence/ Home / MeitY/ MIB / MoHUA/ MoRT&H
3. Member (Services)/ Member (Technology)/ Member (Finance)/ DG (Telecom) DoT
4. Principal Scientific Adviser (PSA) to the Government of India
5. Chairman TRAI/ Chairman DRDO
6. DG ICMR/ DG CDAC/ DG BIS/
7. CEO NeGD/ CEO CDOT/ CEO Prasar Bharati/ DG NTIPRIT
8. Directors of all IITs/ VC DIAT

Standard for Assessing and Rating Robustness of Artificial Intelligence Systems
in Telecom Networks and Digital Infrastructure
Questionnaire
A. Respondent details:
A1. Respondent type (Individual/ Academic institution/ Industry/ Association/ Others)
A2. NameA3. Designation
A4. Organisation
A5. Headquarters
A6. Turnover
B. Need for a Standard for assessing AI Robustness for telecom networks and digital infrastructure:
B1. What are the various use cases/applications of AI in telecom networks and other digitalinfrastructure?
B2. What new applications of AI in telecom networks and digital infrastructure are expected in
the coming years?
B3. What risks are anticipated due to the current and future use of AI in telecom networks anddigital infrastructure?
B4. When evaluating the robustness of AI systems, which aspects or dimensions do you consider
most important, such as availability, accountability, explainability, fairness, privacy,reliability, resilience, safety, scalability, security, trust, and transparency?
B5. How can one assess whether an AI system has a sufficient fallback plan for adversarial
attacks or unexpected situations? How can real-world challenges be simulated during
testing?
B6. What roles are envisioned for government, standards organisations, and regulators inensuring AI robustness in telecom networks and digital infrastructure?
C. Contours of a possible standard for assessing AI robustness:
C1. How can AI systems be categorised to facilitate robustness assessment?
C2. What essential steps or phases should be standardised for assessing AI system robustness intelecom?
C3. What key metrics or performance indicators should be considered when evaluating AI
system robustness?
C4. Are there existing industry standards or guidelines regarding AI robustness? What methods
are considered for evaluating robustness of the AI systems currently?
C5. What key features should a standard for assessing AI systems for robustness, specificallyfocused on telecom networks and other digital infrastructure, include?
C6. What considerations should be taken into account to ensure that the standard for assessing
AI robustness remains adaptable to future advancements in AI and telecom technologies?
The responses to this questionnaire will serve as inputs for the proposed new standard, and their analysis may also be utilized intechnical/research publications.